This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our example_isolates data set. All patient names are created using online surname generators and are only in place for practice purposes.
A data.frame with 500 observations and 53 variables:
ID of the sample
ID of the specimen
Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using
Country of origin
Name of laboratory
Fictitious last name of patient
Fictitious initial of patient
Fictitious gender of patient
Fictitious age of patient
Age group, can also be looked up using
Date of admission
Date of hospital admission
Date when specimen was received at laboratory
Specimen type or group
Specimen type (Numeric)
Reason of request with Differential Diagnosis
ID of isolate
Type of microorganism, can also be looked up using
Serotype of microorganism
Microorganism produces beta-lactamase?
Microorganism produces extended spectrum beta-lactamase?
Microorganism produces carbapenemase?
MRSA screening test
Microorganism is possible MRSA?
Inducible clindamycin resistance
Clindamycin can be induced?
Date of data entry
Date this data was entered in WHONET
28 different antibiotics. You can lookup the abbreviations in the antibiotics data set, or use e.g.
ab_name("AMP") to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this
AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.
On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR data analysis, the complete documentation of all functions and an example analysis using WHONET data.